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Aim: We aimed to develop the first references for body height, body weight and body mass index (BMI) for boys based on the individual developmental tempo with respect to their voice break status. Methods: We re-analysed data from the German Health Interview and Examination Survey for Children and Adolescents (KiGGS study) on body height, body weight and body mass index based on the voice break, or mutation, in 3956 boys aged 10-17 years. We used the LMS method to construct smoothed references centiles for the studied variables in premutational, mutational and postmutational boys. Results: Body height, body weight and BMI differed significantly (p < 0.001) between the different stages of voice break. On average, boys were 5.9 cm taller, 5.8 kg heavier and had a 0.7 kg/m(2) higher BMI with every higher stage of voice break. Currently used growth references for chronological age in comparison with maturity-related references led to an average of 5.4% of boys being falsely classified as overweight.
Background: Clinicians often refer anthropometric measures of a child to so-called “growth standards” and “growth references. Over 140 countries have meanwhile adopted WHO growth standards.
Objectives: The present study was conducted to thoroughly examine the idea of growth standards as a common yardstick for all populations. Weight depends on height. We became interested in whether also weight-for-height depends on height. First, we studied the age-group effect on weight-for-height. Thereafter, we tested the applicability of weight-for-height references in short and in historic populations.
Sample and Methods: We analyzed body height and body weight and weight-for-height of 3795 healthy boys and 3726 healthy girls aged 2 to 5 years measured in East-Germany between 1986 and 1990.
We chose contemporary height and weight charts from Germany, the UK, and the WHO growth chart and compared these with three geographically commensurable growth charts from the end of the 19th century.
Results: We analyzed body height and body weight and weight-for-height of 3795 healthy boys and 3726 healthy girls aged 2 to 5 years measured in East-Germany between 1986 and 1990.
We chose contemporary height and weight charts from Germany, the UK, and the WHO growth chart and compared these with three geographically commensurable growth charts of the end of the 19th century.
Conclusion: Weight-for-height depends on age and sex and apart from the nutritional state, reflects body proportion and body built particularly during infancy and early childhood. Populations with a relatively short average height are prone to high values of weight-for-height for arithmetic reasons independent of the nutritional state.
BACKGROUND/OBJECTIVES: We studied the association of body weight and weight variability among populations from different geographic, historic and socioeconomic background. SUBJECTS/METHODS: We reanalyzed data from 833 growth studies of 78 different countries from 1920 to 2013. We used data from two age groups-infants (age 2 years) and juvenile (age 7 years)-and divided the studies into two geographic-socioeconomic groups. RESULTS: Multiple regressions showed significant interactions between weight, sex, historic year of study, continent and within-study standard deviation. Multiple regression revealed R-2 = 0.256 (P<0.001) at age 2 years and R-2 = 0.478 (P<0.001) at age 7 years. Although infants and juveniles in more affluent countries are heavier than children in less affluent countries (P<0.001), the within-study standard deviation of the two geographic-socioeconomic groups differs at age 7 years (P<0.001) but not at age 2 years (P>0.15). CONCLUSIONS: The general impression that prosperous conditions lead to growth improvements in height and weight appears to be true only at a large scale: wealthy countries have tall and heavy children. At small scale, the situation is different. Whereas economic and nutritional improvements can exhibit substantial effects in weight gains, the discrepancy between the within-population variation in height and weight strongly suggests that height gains and weight gains are subject to different regulations.
Twenty-four scientists met at Aschauhof, Altenhof, Germany, to discuss the associations between child growth and development, and nutrition, health, environment and psychology. Meta-analyses of body height, height variability and household inequality, in historic and modern growth studies published since 1794, highlighting the enormously flexible patterns of child and adolescent height and weight increments throughout history which do not only depend on genetics, prenatal development, nutrition, health, and economic circumstances, but reflect social interactions. A Quality of Life in Short Stature Youth Questionnaire was presented to cross-culturally assess health-related quality of life in children. Changes of child body proportions in recent history, the relation between height and longevity in historic Dutch samples and also measures of body height in skeletal remains belonged to the topics of this meeting. Bayesian approaches and Monte Carlo simulations offer new statistical tools for the study of human growth.
Background:
Physical growth of children and adolescents depends on the interaction of genetic and environmental factors e.g. diet and living conditions. Aim: We aim to discuss the influence of socioeconomic situation, using income inequality and GDP per capita as indicators, on body height, body weight and the variability of height and weight in infants and juveniles.
Material and methods:
We re-analyzed data from 439 growth studies on height and weight published during the last 35 years. We added year-and country-matched GDP per capita (in current US$) and the Gini coefficient for each study. The data were divided into two age groups: infants (age 2) and juveniles (age 7). We used Pearson correlation and principal component analysis to investigate the data.
Results:
Gini coefficient negatively correlated with body height and body weight in infants and juveniles. GDP per capita showed a positive correlation with height and weight in both age groups. In infants the standard deviation of height increases with increasing Gini coefficient. The opposite is true for juveniles. A correlation of weight variability and socioeconomic indicators is absent in infants. In juveniles the variability of weight increases with declining Gini coefficient and increasing logGDP per capita.
Discussion:
Poverty and income inequality are generally associated with poor growth in height and weight. The analysis of the within-population height and weight variations however, shows that the associations between wealth, income, and anthropometric parameters are very complex and cannot be explained by common wisdom. They point towards an independent regulation of height and weight.
Background: Over 60 years ago the biggest drug catastrophe in Germany took place. The drug thalidomide, sold by the German pharmaceutical company Chemie Grunenthal GmbH starting in 1957 under the name "Contergan", caused severe birth defects in newborns. Chemie Grunenthal withdraw Contergan in 1961. Until nearly 30 years later in 1988 there were already over 10.000 children born with severe birth defects (e.g. dysmelia, amelia, congenital heart defect). Due to the high variability of the birth defects caused by thalidomide, later called thalidomide embryopathy, there is still no detailed information about the proportions of limbs. Aim: The aim is to develop reference centiles for limb measurements of men and women aged 19-70 years old. Method: For the calculation, data of healthy men and women (m = 2984, f = 2838) from former East Germany were used and centiles using the LMS-method were developed. Results: Centile tables for arm and leg length of men and women are presented in the results. The variability is small due to a homogeneous distribution of the measurements. A test with randomly chosen patient data shows that women under 171 cm stature and men under 180 cm stature can be assessed correctly. A severe shortening of limbs can be detected with this method.
Meeting Reports
(2019)
Thirty-one scientists met at Aschauhof, Germany to discuss the role of beliefs and self-perception on body size. In view of apparent growth stimulatory effects of dominance within the social group that is observed in social mammals, they discussed various aspects of competitive growth strategies and growth adjustments. Presentations included new data from Indonesia, a cohort-based prospective study from Merida, Yucatan, and evidence from recent meta-analyses and patterns of growth in the socially deprived. The effects of stress experienced during pregnancy and adverse childhood events were discussed, as well as obesity in school children, with emphasis on problems when using z-scores in extremely obese children. Aspects were presented on body image in African-American women, and body perception and the disappointments of menopause in view of feelings of attractiveness in different populations. Secular trends in height were presented, including short views on so called 'racial types' vs bio-plasticity, and historic data on early-life nutritional status and later-life socioeconomic outcomes during the Dutch potato famine. New tools for describing body proportions in patients with variable degrees of phocomelia were presented along with electronic growth charts. Bio-statisticians discussed the influence of randomness, community and network structures, and presented novel tools and methods for analyzing social network data.
Twenty-two scientists met at Krobielowice, Poland, to discuss the impact of the social environment, spatial proximity, migration, poverty, but also psychological factors such as body perception and satisfaction, and social stressors such as elite sports, and teenage pregnancies, on child and adolescent growth. The data analysis included linear mixed effects models with different random effects, Monte Carlo analyses, and network simulations. The work stressed the importance of the peer group, but also included historic material, some considerations about body proportions, and growth in chronic liver, and congenital heart disease.
Background
The association between bivariate variables may not necessarily be homogeneous throughout the whole range of the variables. We present a new technique to describe inhomogeneity in the association of bivariate variables.
Methods
We consider the correlation of two normally distributed random variables. The 45° diagonal through the origin of coordinates represents the line on which all points would lie if the two variables completely agreed. If the two variables do not completely agree, the points will scatter on both sides of the diagonal and form a cloud. In case of a high association between the variables, the band width of this cloud will be narrow, in case of a low association, the band width will be wide. The band width directly relates to the magnitude of the correlation coefficient. We then determine the Euclidean distances between the diagonal and each point of the bivariate correlation, and rotate the coordinate system clockwise by 45°. The standard deviation of all Euclidean distances, named “global standard deviation”, reflects the band width of all points along the former diagonal. Calculating moving averages of the standard deviation along the former diagonal results in “locally structured standard deviations” and reflect patterns of “locally structured correlations (LSC)”. LSC highlight inhomogeneity of bivariate correlations. We exemplify this technique by analyzing the association between body mass index (BMI) and hip circumference (HC) in 6313 healthy East German adults aged 18 to 70 years.
Results
The correlation between BMI and HC in healthy adults is not homogeneous. LSC is able to identify regions where the predictive power of the bivariate correlation between BMI and HC increases or decreases, and highlights in our example that slim people have a higher association between BMI and HC than obese people.
Conclusion
Locally structured correlations (LSC) identify regions of higher or lower than average correlation between two normally distributed variables.
Background
The association between bivariate variables may not necessarily be homogeneous throughout the whole range of the variables. We present a new technique to describe inhomogeneity in the association of bivariate variables.
Methods
We consider the correlation of two normally distributed random variables. The 45° diagonal through the origin of coordinates represents the line on which all points would lie if the two variables completely agreed. If the two variables do not completely agree, the points will scatter on both sides of the diagonal and form a cloud. In case of a high association between the variables, the band width of this cloud will be narrow, in case of a low association, the band width will be wide. The band width directly relates to the magnitude of the correlation coefficient. We then determine the Euclidean distances between the diagonal and each point of the bivariate correlation, and rotate the coordinate system clockwise by 45°. The standard deviation of all Euclidean distances, named “global standard deviation”, reflects the band width of all points along the former diagonal. Calculating moving averages of the standard deviation along the former diagonal results in “locally structured standard deviations” and reflect patterns of “locally structured correlations (LSC)”. LSC highlight inhomogeneity of bivariate correlations. We exemplify this technique by analyzing the association between body mass index (BMI) and hip circumference (HC) in 6313 healthy East German adults aged 18 to 70 years.
Results
The correlation between BMI and HC in healthy adults is not homogeneous. LSC is able to identify regions where the predictive power of the bivariate correlation between BMI and HC increases or decreases, and highlights in our example that slim people have a higher association between BMI and HC than obese people.
Conclusion
Locally structured correlations (LSC) identify regions of higher or lower than average correlation between two normally distributed variables.